A day in the life of Nice Ride bikes

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The green bikes have come to downtown St. Paul with this week’s installation of 25 Nice Ride stations, just in time for the Twin Cities Bike Walk Week.

It’s the latest expansion of the popular bike rental system that lets subscribers pedal between automated, solar-powered stations scattered throughout Minneapolis and St. Paul.

The system began in Minneapolis two years ago. With the St. Paul expansion, there are now 146 stations with 1,328 bikes available stretching between Minneapolis’ Uptown and St. Paul’s West Side.

Daily, weekly or annual subscriptions are required, allowing free rides of up to 30 minutes, with trip fees added after the first half-hour.

Below, we’ve animated a day in the life of Nice Ride bikes in the Twin Cities. Click play and zoom into the map to see how bikes move between stations throughout a 24-hour period (based on 2011 data).

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2011 station; press to see name.

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Model routes taken by cyclists over 2011, weighted by popularity.

Bike routing is not actual; the routes are modeled with OpenStreetMap data weighted for cyclists. The animation is a model of what was determined to be the "most average" day of 2011 which was May 18, 2011 at 4:30AM to May 19, 2011 at 4:30AM.

Hey Richard. Good question. We do not have data for the actual routes that bikes were taken; I do not belive Nice Ride has this data, or at least has not made it public (I do not know if there are GPS units on the bikes). We did have start and end points for every ride taken, and therefore we could model a mostly ideal path the bike would take. We utilized data from Open Street Map and utilized a technology called Routino to create these routes. I will be writing up a more in-depth story on how this piece was put together if you are interested in learning more.

Alan / Joe,
I’ve seen some maps from other systems made using Routino and OSM. I’ve been waiting for someone local to take it up using our data. The data released last year is the most detailed available. The bikes are not equipped with GPS transponders. I plan to continue making Nice Ride usage data available in the future for uses such as this map. Projects like this are of great benefit to us for use in future planning and system optimization. I’m looking forward to seeing more.

This is really cool—I have used the bikes that are based next to my office in NE but have always wondered how much use they get around the city. This is a great visual representation. Nice job guys! And hi Alan 🙂

This is a fantastic animation and a perfect use of data visualization! A few comments/questions. I know the program was expanded into Saint Paul last year. Is the animation from a specific day that preceded Saint Paul being included in the system? It also appears that there are no rides in North Mpls. Also, it seems that the “popularity” (however defined) in terms of route choice might is weighted too heavily over of the shortest pratical distance for riders. For example, it appears that anyone going from DT Mpls to Uptown travels around Cedar Lake rather than take Bryant, Lyndale, or Hennepin (since there are no stations along Kenilworth or Cedar Lake). I would argue that most people would not take this route. Great work, and thanks for the update on your methods!

Thanks Timothy. How we built this may help answer some of these questions in more depth. I’ll address some of your comments here, though. Overall, the static parts of the maps, routes and stations, are analysis from the whole year, while the animation is simulating a single day.

The stations (green dots) and the routes (blue lines) are taken from the whole 2011 year. The weight of the routes (popularity) is based on the years’ analysis of which routes were taken most often (ie Station A to Station B) through out the whole year. The routes were modeled as best as they could be given that we only had start and end points and using Open Street Map as our path database; these are not meant to be the most ideal or suggestions of any kind, but simly the best guess we could make with the tools we had.

The animation is based on the “most average” day which was May 18, 2011 which was before all the stations were installed. We determined “average” as the average bike density (given 5 minute intervals) throughout the year.

We have discussed putting together more animations to show other days (days later in the year would have trips in St. Paul, for instance). This would require some significant technical work as this piece already pushes the limits of many of our audience’s computers.